Wireless monitoring and digital twinning method and system for service state of pipeline system

Abstract

The invention relates to a pipeline system service state wireless monitoring and digital twinning method and system. The method comprises the following steps: establishing communication connection with each monitoring module through a wireless communication network; wherein the wireless communication network is composed of a plurality of wireless gateways, and the monitoring module is used for being arranged on a preset monitoring point of a pipeline system and sensing monitoring data of the corresponding monitoring point; performing time-space synchronization control on each monitoring module; acquiring sensing data output after the monitoring modules are synchronized; real-time structural mechanical simulation is carried out on the actual operation state of the pipeline system according to monitoring data of the monitoring modules, and digital twinning of the actual operation state of the pipeline system is achieved; and performing diagnosis processing according to the digital twinning result, and outputting a diagnosis result. Monitoring data of each monitoring point of the pipeline system can be obtained in a wireless communication mode, communication cable laying is not needed, and the problems that construction is difficult, equipment mistaken touch is likely to be caused, and maintenance difficulty is large are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of nuclear power plant equipment monitoring, and particularly relates to a pipeline system service state wireless monitoring and digital twin method and system. BACKGROUND

[0002] The pipeline system is an important part of the power industry generator set and chemical device, and the support hanger is widely used as a supporting device of the pipeline system. Among them, the support hanger bearing the weight of the pipeline includes variable force spring support hanger, constant force spring support hanger, guide support hanger and rigid hanger. At present, the pipeline system rupture accidents occur frequently in the power industry, especially the high temperature and high pressure pipeline, which may also cause personal safety accidents. The periodic inspection and daily inspection based on the traditional technology cannot timely find hidden defects, which often leads to the deterioration of the pipeline state and causes accidents.

[0003] The existing online monitoring technology mainly adopts a wired data transmission mode. However, due to the large space span of the pipeline system of the generator set and the large number of support hangers, a large number of data transmission cables need to be arranged for the wired monitoring system, which leads to complex system construction, high cost, and safety hazards such as equipment misoperation during the arrangement process. SUMMARY

[0004] The technical problem to be solved by the present application is to provide a pipeline system service state wireless monitoring and digital twin method and system.

[0005] The technical solution adopted by the present application to solve the technical problem is: a pipeline system service state wireless monitoring and digital twin method is constructed, comprising: A wireless communication network is established to communicate with each monitoring module; wherein the wireless communication network is composed of multiple wireless gateways, and the monitoring module is arranged on the preset monitoring point of the pipeline system and senses the monitoring data of the corresponding monitoring point; Each monitoring module is controlled in time and space synchronization; The sensing data output by each monitoring module after synchronization is acquired; The actual running state of the pipeline system is simulated in real time according to the monitoring data of each monitoring module, and the digital twin of the actual running state of the pipeline system is realized; The diagnosis result is output according to the digital twin result.

[0006] Preferably, the time and space synchronization control of each monitoring module comprises: A time stamp is broadcasted to each wireless gateway; The wireless gateway is controlled to send a time correction pulse to the corresponding wireless gateway in a TDMA time slot allocation mode, so that each monitoring module is synchronized.

[0007] Preferably, in the step of acquiring the sensing data output by each of the monitoring modules after synchronization, the method further comprises: constructing a minimum spanning tree topology according to the distribution of each of the monitoring modules, and acquiring the sensing data output by each of the monitoring modules based on the minimum spanning tree topology.

[0008] Preferably, in the step of acquiring the sensing data output by each of the monitoring modules after synchronization, the method further comprises: monitoring the interference intensity of a default frequency band in real time; determining whether the interference intensity is greater than a preset intensity threshold; when the interference intensity is greater than the preset intensity threshold, controlling the communication frequency band of the wireless communication network to switch to a backup frequency band; wherein the default frequency band includes 2.4 GHz or 5.8 GHz, and the backup frequency band includes 868 MHz or 915 MHz.

[0009] Preferably, the monitoring data includes load data, displacement data, and temperature data. The method further comprises: establishing a finite element model based on the finite element method and the pipeline system; establishing a mapping relationship between all preset monitoring points of the pipeline system and corresponding nodes in the finite element model; inputting the monitoring data of each of the monitoring modules into the finite element model to obtain dynamic actual operating state data of each pipe section in the pipeline system through real-time calculation and analysis; The method further comprises: performing defect identification processing and trend prediction processing on each of the pipe sections according to the dynamic actual operating state data.

[0010] Preferably, the actual operating state data includes displacement change data of each pipe section in the pipeline system, load change data and displacement change data of each rigid support hanger on each pipe section, load change data and spring displacement change data of each spring support hanger on each pipe section, and expansion change data and temperature change data of each guide support hanger on each pipe section. The defect identification processing comprises: According to the actual operation state data, the following processing is performed: when it is judged that the load variation of all the supports and hangers on the pipe section within a first set time is greater than a load instantaneous fluctuation threshold and it is judged that the displacement variation of the pipe section within the first set time is greater than a displacement instantaneous fluctuation threshold, if the above two judgment results are yes, it is determined that the pipe section has transient impact; if the load of all the supports and hangers and the displacement of the pipe section within a second set time all appear continuous fluctuation, if yes, it is determined that the pipe section has steady-state vibration; if it is judged that the load of the spring support and hanger is greater than an overload threshold, if yes, it is determined that the spring support and hanger is overloaded; the expansion and temperature change curve of the guide support and hanger is fitted, the expansion and temperature change curve is compared with a preset expansion amount comparison curve, and whether the pipeline has expansion is determined according to the comparison result.

[0011] Preferably, the trend prediction processing includes: According to the actual operation state data, the following processing is performed: fitting the real-time curve of the load and displacement change of each spring support and hanger, obtaining a plurality of real-time curves, comparing each real-time curve with the corresponding theoretical curve, and determining whether the spring stiffness of each spring support and hanger deviates according to the comparison result; if it is judged that the displacement settlement of the pipe section within a third set time is greater than a first settlement threshold and it is judged that the displacement settlement of the pipe section within a fourth set time is greater than a second settlement threshold, if any of the above judgment results is yes, it is determined that the pipe section has a sinking trend.

[0012] Preferably, the pipeline system service state wireless monitoring and digital twin method further includes: A three-dimensional model of the pipeline system is established; Based on the diagnosis result, the preset monitoring points with defects and abnormal trends in the three-dimensional model are highlighted.

[0013] The application also constructs a pipeline system service state wireless monitoring and digital twin system, which includes a monitoring platform, a plurality of wireless gateways and a plurality of monitoring modules; Each monitoring module is arranged on a preset monitoring point of the pipeline system to sense the monitoring data of the corresponding monitoring point and send the monitoring data in a wireless communication mode; Each wireless gateway constitutes a wireless communication network, which is in communication connection with each monitoring module and is used for sending the monitoring data sensed by each monitoring module to the monitoring platform; The monitoring platform includes a processor, which realizes the pipeline system service state wireless monitoring and digital twin method described above when executing a computer program.

[0014] Preferably, the monitoring module comprises a load sensor, a distance sensor, a temperature sensor, an electric energy storage unit, a data storage unit, a wireless communication unit and a voltage stabilizing unit. The load sensor is arranged at a preset monitoring point to sense a load received by the corresponding preset monitoring point and output load data. The distance sensor is arranged at a preset monitoring point to sense a displacement of the corresponding preset monitoring point and output displacement data. The temperature sensor is arranged at a preset monitoring point to sense a temperature of the corresponding preset monitoring point and output temperature data. The electric energy storage unit is configured to output a power supply voltage. The data storage unit is electrically connected with the load sensor and the distance sensor and is configured to store the load data and the displacement data. The wireless communication unit is electrically connected with the data storage unit and is configured to send the load data and the displacement data to the wireless gateway. The voltage stabilizing unit is electrically connected with the load sensor, the distance sensor, the temperature sensor, the electric energy storage unit, the data storage unit and the wireless communication unit and is configured to convert the voltage output by the electric energy storage unit into a stable voltage and supply power to each unit.

[0015] The embodiments of the present application obtain monitoring data of each monitoring point of the pipeline system through wireless communication, without the need for laying communication cables, thereby solving the problems of difficult construction, easy device collision and difficult maintenance, reducing the difficulty and cost of laying, and diagnosing whether the pipeline system has defects or abnormal trends according to the monitoring data of each monitoring point, thereby providing protection for maintaining the safety of the pipeline system. BRIEF DESCRIPTION OF DRAWINGS

[0016] The present application will be further described below with reference to the accompanying drawings and examples, wherein: Figure 1 is a program flowchart of the pipeline system service state wireless monitoring and digital twin method in some embodiments of the present application; Figure 2 is a program flowchart of the diagnosis process in some embodiments of the present application; Figure 3 is a structural schematic diagram of the pipeline system service state wireless monitoring and digital twin system in some embodiments of the present application. DETAILED DESCRIPTION

[0017] In order to have a clearer understanding of the technical features, objectives and effects of the present application, the specific embodiments of the present application will be described in detail with reference to the accompanying drawings.

[0018] It should be noted that the flowchart shown in the accompanying drawings is only an exemplary illustration, and is not necessarily required to include all contents and operations / steps, nor is it necessarily required to be executed in the order described. For example, some operations / steps can be further decomposed, and some operations / steps can be combined or partially combined, so the actual execution order can be changed according to actual conditions.

[0019] The block diagram shown in the accompanying drawings is only a functional entity, and does not necessarily correspond to a physically independent entity. That is, the functional entity can be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0020] Figure 1 is a program flowchart of a pipeline system service state wireless monitoring and digital twin method in some embodiments of the present application. The monitoring method can obtain monitoring data of each monitoring point of the pipeline system through wireless communication, without the need for communication cable laying, solving the problems of difficult construction, easy to cause equipment mis-touching and difficult maintenance, etc., helping to reduce the laying difficulty and cost, and can diagnose whether the pipeline system has defects or abnormal trends according to the monitoring data of each monitoring point, providing protection for maintaining the safety of the pipeline system.

[0021] The pipeline system service state wireless monitoring and digital twin method can be used for a processor in a monitoring platform, as shown in Figure 1 The method can include steps S10, S20, S30, S40 and S50.

[0022] Step S10 includes establishing a communication connection with each monitoring module through a wireless communication network. The wireless communication network is composed of multiple wireless gateways, and the monitoring module is used to be arranged on a preset monitoring point of the pipeline system and to sense monitoring data of the corresponding monitoring point.

[0023] In some embodiments, the wireless gateway can be an existing gateway supporting NB-IoT / 4G dual mode, and each wireless gateway can be communicatively connected to multiple monitoring modules, usually 10 to 30 monitoring modules.

[0024] In order to improve the transmission efficiency of the monitoring data and make the transmission delay less than 100ms, in some embodiments, in step S10, the method can further include: communicating with the wireless gateway through a 5G network. In this way, the monitoring platform can simultaneously and quickly obtain monitoring data of multiple monitoring modules.

[0025] The preset monitoring points include, but are not limited to, any position on the pipe segment body, any position of the support hanger on the pipe segment (such as the spring of the spring support hanger, the support hanger body, etc.). In some embodiments, the monitoring module can include a load sensor, a distance measuring sensor, and a temperature sensor, and correspondingly, the monitoring data includes load data, displacement data, and temperature data. It can be understood that, for the preset monitoring points on the pipe segment body, the load data includes the load information of the entire pipe segment, and the distance measuring sensor includes the three-direction displacement information (vertical drop and horizontal displacement) of the pipe segment. For the preset monitoring points on the spring of the spring support hanger, the load data includes the load information of the entire spring support hanger, and the displacement data includes the displacement information of the spring of the spring support hanger. For the preset monitoring points on the rigid support hanger body, the load data includes the load information of the entire rigid support hanger, and the displacement data includes the displacement information of the entire rigid support hanger. For the preset monitoring points on the guide support hanger, the displacement data includes the expansion information of the guide support hanger, and the temperature data includes the temperature information of the guide support hanger.

[0026] It should be noted that, since the expansion of the mechanical components is closely related to the temperature, and the expansion of the guide support hanger can cause jamming, the temperature sensor is mainly used to measure the temperature information of the guide support hanger, and of course, in order to monitor the temperature of each mechanical component, the relevant temperature information can also be collected at other position monitoring points (including the pipe body, the spring support hanger, etc.).

[0027] In some embodiments, the distance measuring sensor can measure the expansion information of the guide support hanger by measuring the distance between the guide rail of the guide support hanger and the body of the distance measuring sensor.

[0028] In some embodiments, the monitoring module can be communicatively connected with the wireless gateway through ZigBee communication technology.

[0029] Step S20 includes: performing time and space synchronization control on each monitoring module. It can be understood that, the number of monitoring modules is large, and the wireless communication is affected by factors such as signal quality fluctuation and interference, which can cause the monitoring data to be out of synchronization, and if the monitoring data is out of synchronization, it will cause the diagnostic confidence of the subsequent steps to decrease, therefore, this step will periodically perform time and space synchronization control on each monitoring module, so as to ensure that the time error of the sensing data output by each monitoring module is not greater than 1 ms.

[0030] In some embodiments, the time and space synchronization control can be achieved by performing the following steps: broadcasting a time stamp to each wireless gateway; and controlling the wireless gateway to send a time correction pulse to the corresponding wireless gateway in a TDMA time slot allocation manner, so that each monitoring module is synchronized.

[0031] The embodiment periodically broadcasts a unified timestamp (with an accuracy of ±0.1 μs, such as a GPS / Beidou timestamp), so that each wireless gateway can automatically correct the time according to the timestamp, thereby keeping the time synchronized. In addition, each wireless gateway sends a time correction pulse to all the monitoring modules connected thereto in a TDMA time slot allocation manner. When a monitoring module receives the time correction pulse, it automatically corrects the time according to the time correction pulse and a preset software program, so that all the monitoring modules can achieve synchronized monitoring data. In addition, TDMA time slot allocation is a mature technology and can efficiently achieve time synchronization of terminals. For details, refer to the prior art, which will not be described here.

[0032] Step S30 includes: obtaining the sensing data output by each monitoring module after synchronization.

[0033] In some embodiments, the following steps can also be performed in the process of obtaining the sensing data output by each monitoring module after synchronization: constructing a minimum spanning tree topology according to the distribution of each monitoring module, and obtaining the sensing data output by each monitoring module based on the minimum spanning tree topology.

[0034] In the embodiment, the minimum spanning tree topology is used to transmit the monitoring data sensed by each monitoring module to the monitoring platform in the shortest possible path, that is, the embodiment can reduce the relay hop count in the monitoring data transmission process and improve the transmission efficiency of the sensing data by optimizing the communication line between each monitoring module and the wireless gateway. It should be noted that the construction of the minimum spanning tree topology is a mature technology, and for details, refer to the prior art, which will not be described here.

[0035] In some embodiments, the following steps can also be performed in the process of obtaining the sensing data output by each monitoring module after synchronization: monitoring the interference intensity of the default frequency band in real time; determining whether the interference intensity is greater than a preset intensity threshold; and when the interference intensity is greater than the preset intensity threshold, switching the communication frequency band of the wireless communication network to the backup frequency band.

[0036] In the embodiment, the default frequency band can include commonly used commercial frequency bands such as 2.4 GHz or 5.8 GHz, which has the advantages of being mature and easy to implement. However, since the user usage of the default frequency band is large, interference is likely to occur. Therefore, when the interference intensity of the default frequency band is greater than the preset intensity threshold, the default frequency band is actively avoided, and the backup frequency band is used, so as to avoid the reduction of the monitoring data transmission efficiency due to network congestion.

[0037] In some embodiments, the backup frequency band can include industrial unlicensed frequency bands such as 868 MHz or 915 MHz.

[0038] Step S40 comprises: performing real-time structural mechanics simulation on the actual operation state of the pipeline system according to the monitoring data of each monitoring module, so as to realize digital twinning of the actual operation state of the pipeline system.

[0039] In some embodiments, the digital twinning can be realized by performing steps S401 to S403 as shown. Figure 2

[0040] Step S401 comprises: establishing a finite element model based on the finite element method and the pipeline system. In this step, the finite element model can be established by a finite element software (such as CAESAR II, PIPES) based on the three-dimensional structure of the pipeline system and taking the pipe segment as a sub-region, wherein the finite element model contains boundary condition nodes corresponding to the plurality of preset monitoring points of the pipeline system.

[0041] Step S402 comprises: establishing a mapping relationship between all preset monitoring points of the pipeline system and corresponding nodes in the finite element model. The purpose of this step is to establish a one-to-one mapping relationship between all preset monitoring points of the pipeline system and boundary condition nodes in the finite element model, so as to perform finite element analysis and calculation.

[0042] Step S403 comprises: inputting the monitoring data of each monitoring module into the finite element model to obtain the actual operation state data of the pipeline system through real-time calculation and analysis.

[0043] In this step, when all monitoring data are input into the finite element model, the finite element model will solve the displacement information, load information and temperature information of each boundary condition node based on a preset function, so as to obtain the actual operation state data of each pipe segment (i.e. the digital twinning result). Correspondingly, the actual operation state data can include the displacement change data of each pipe segment in the pipeline system, the load change data and displacement change data of each rigid support hanger on each pipe segment, the load change data and spring displacement change data of each spring support hanger on each pipe segment, and the expansion change data and temperature change data of each guide support hanger on each pipe segment. It should be noted that the change data includes all change records of the physical information of the monitoring point changing with time, for example, the displacement change data of the pipe segment includes all displacement change records of the pipe segment in the current detection period. Wherein, the detection period can be set by the worker according to the actual situation.

[0044] Step S50 comprises: performing diagnosis processing according to the digital twinning result and outputting the diagnosis result.

[0045] In some embodiments, in step S50, the diagnosis processing can be realized by performing the following steps: performing defect identification processing and trend prediction processing on each pipe segment according to the actual operation state data.

[0046] ​In some embodiments, the defect identification process in step S50 can include: performing steps S4041 to S4044 according to the actual operation state data.

[0047] Step S4041 includes: determining, according to the load change data of the supports (including spring supports, rigid supports and guide supports), whether the change amount of the load of all supports on the pipe section within a first set time is greater than a load transient fluctuation threshold value, and determining, according to the displacement change data of the pipe section, whether the change amount of the displacement of the pipe section within the first set time is greater than a displacement transient fluctuation threshold value, and if both determination results are yes, determining that the pipe section has transient impact.

[0048] In this step, when the change amount of the load of all supports on the pipe section within the first set time is greater than the load transient fluctuation threshold value and the change amount of the displacement of the pipe section within the first set time is greater than the displacement transient fluctuation threshold value, it is indicated that the pipe section has suffered transient impact.

[0049] Step S4042 includes: determining, according to the load change data of the supports (including spring supports, rigid supports and guide supports), whether the load of all supports has continuous fluctuation within a second set time, and determining, according to the displacement change data of the pipe section, whether the displacement of the pipe section has continuous fluctuation within the second set time, and if both determination results are yes, determining that the pipe section has steady-state vibration. The first set time is less than the second set time.

[0050] In some embodiments, whether the pipe section has steady-state vibration can be determined by: fitting a load change curve according to the load change data of all supports of the pipe section to obtain a plurality of load change curves; fitting a displacement change curve according to the displacement change data of the pipe section; performing fluctuation identification on the displacement change curve and each load change curve based on an image recognition algorithm to determine whether the load change curve corresponding to each support has continuous fluctuation and whether the displacement of the pipe section has continuous fluctuation; and when the load change curve corresponding to each support and the displacement change curve all have continuous fluctuation, determining that the pipe section has steady-state vibration.

[0051] Specifically, whether the corresponding curve has continuous fluctuation can be determined by identifying, through an existing image recognition algorithm, whether there is a sawtooth wave with continuous fluctuation in a set range in the displacement or load change curve.

[0052] Step S4043 includes: determining, according to the load change data of the spring support, whether the load of the spring support is greater than an overload threshold value, and if yes, determining that the spring support is overloaded.

[0053] Step S4044 includes fitting an expansion and temperature change curve of the guide support according to the expansion change data and the temperature change data of the guide support, comparing the expansion and temperature change curve with a preset expansion amount comparison curve, and determining whether the pipeline has expansion according to a comparison result.

[0054] In this step, the expansion of the guide support is related to its temperature, the expansion and temperature change curve can represent an actual change relationship between the expansion amount of the guide support and the temperature, and the expansion amount comparison curve is a linear relationship curve of the expansion amount and the temperature which is fitted in advance based on the design parameters of the guide support (which can be obtained from a supplier). The expansion and temperature change curve and the expansion amount comparison curve can be analyzed for coincidence degree to obtain a coincidence degree. When the coincidence degree is less than a coincidence threshold, it is determined that the pipeline has expansion.

[0055] In some embodiments, the trend prediction process can include: according to the actual operation state data, the following processing is performed: fitting a real-time curve of the load and displacement change of each spring support according to the load change data and the spring displacement change data of each spring support, obtaining a plurality of real-time curves, comparing each real-time curve with the corresponding theoretical curve respectively, and determining whether the spring of each spring support has a spring stiffness deviation trend according to a comparison result; judging whether the displacement of the pipe section has a settlement amount greater than a first settlement threshold in a third set time and whether the displacement of the pipe section has a settlement amount greater than a second settlement threshold in a fourth set time according to the displacement change data of the pipe section. If any of the above determination results is yes, it is determined that the pipe section has a sinking trend.

[0056] In this embodiment, the real-time curve of each spring support is fitted from its own load change data and spring displacement change data. Moreover, since the specifications of the springs in the spring supports can be different, the theoretical curve corresponding to each spring support can be different. The theoretical curve can be measured based on Hooke's law after the spring support is installed, or can be obtained from a supplier. Understandably, based on Hooke's law, the compression amount (or displacement) of the spring is theoretically the same under the same load. Therefore, when compared with the theoretical curve, a significant deviation in displacement or load indicates that the spring performance has a degradation trend. In addition, the coincidence degree of the real-time curve and the theoretical curve can also be analyzed to determine whether the spring stiffness of the corresponding spring support has a deviation trend.

[0057] In some embodiments, the third set time can be 1 day, and the first settlement threshold can be 0.5 mm. The third set time can be 1 month, and the second settlement threshold can be 2 mm. Understandably, when the daily settlement amount of the pipe section body is greater than 0.5 mm or the monthly cumulative settlement amount is greater than 2 mm, it indicates that the pipe section body has a sinking trend.

[0058] In some embodiments, the step S404 can further include: determining whether the pipe segment has a sinking trend according to the actual operation state data, including: fitting a displacement-temperature curve according to the displacement change data and the temperature change data of each preset monitoring point, respectively comparing each displacement-temperature curve with a corresponding sinking contrast curve, and determining whether the corresponding preset monitoring point has a significant deviation according to the comparison result; and determining that the pipe segment has a sinking trend when the number of preset monitoring points with a significant deviation reaches a set number and the sinking displacement of these preset monitoring points is greater than a sinking threshold.

[0059] In some embodiments, the step S404 can further include: predicting the remaining life of each pipe segment according to the actual operation state data, including: combining a historical material S-N curve (stress-life curve) of the support hanger, calculating a fatigue damage degree according to a linear cumulative damage rule and load change data of the support hanger, and predicting the remaining life of the corresponding support hanger according to the fatigue damage degree.

[0060] In the present embodiment, the material S-N curve can be fitted by historical monitoring data of the support hanger. The remaining life prediction is a mature technology in the field of material mechanics, and the specific implementation method can refer to the prior art, which will not be described here. It can be understood that predicting the remaining life of the support hanger can effectively predict the trend of the mechanical properties of the pipeline system, which helps to give early warning and intervention before a serious accident occurs and eliminates safety hazards.

[0061] In some embodiments, the pipeline system service state wireless monitoring and digital twin method can further include the following steps: establishing a three-dimensional model of the pipeline system; and highlighting the preset monitoring points with defects and abnormal trends in the three-dimensional model based on the diagnosis result.

[0062] In the present embodiment, the three-dimensional model consistent with the structure and implementation system can be restored according to the design drawings of the pipeline system, and each monitoring point is calibrated in the three-dimensional model and associated with the corresponding finite element according to its position in the real pipeline system. When a preset monitoring point has defects and abnormal trends (such as pipe segment sinking, spring deviation trend, etc.), the preset monitoring point is marked in a special color, for example, red, and the preset monitoring points without defects and abnormal trends are marked in green. In this way, the staff can intuitively observe the preset monitoring points with abnormalities, so as to take warning measures as soon as possible.

[0063] As Figure 3As shown, the application also constructs a pipeline service state wireless monitoring and digital twin system, which comprises a monitoring platform, a plurality of wireless gateways and a plurality of monitoring modules. Each monitoring module is arranged on a preset monitoring point of the pipeline system to sense monitoring data of the corresponding monitoring point and send the monitoring data in a wireless communication manner. The wireless gateways constitute a wireless communication network, which is in communication connection with the monitoring modules and is used for sending the monitoring data sensed by the monitoring modules to the monitoring platform. The monitoring platform comprises a processor, which realizes the pipeline service state wireless monitoring and digital twin method provided by the embodiment of the application when executing a computer program.

[0064] In some embodiments, the monitoring module can comprise a load sensor, a distance measuring sensor, a temperature sensor, an electric energy storage unit, a data storage unit, a wireless communication unit and a voltage stabilizing unit.

[0065] The load sensor is arranged on the preset monitoring point to sense the load received by the corresponding preset monitoring point and output load data. Optionally, the load sensor is an existing MEMS piezoresistive sensor, preferably a MEMS piezoresistive sensor with power consumption not greater than 0.1 mW and load measurement range of 0-200 KN.

[0066] The distance measuring sensor is arranged on the preset monitoring point to sense the displacement of the corresponding preset monitoring point and output displacement data. Optionally, the distance measuring sensor is an existing laser distance measuring sensor, preferably a laser distance measuring sensor with displacement measurement accuracy of ±0.2 mm.

[0067] The temperature sensor is arranged on the preset monitoring point to sense the temperature of the corresponding preset monitoring point and output temperature data.

[0068] The electric energy storage unit is used to output a power supply voltage. The electric energy storage unit can be a battery.

[0069] The data storage unit is electrically connected with the load sensor and the distance measuring sensor, and the data storage unit is used to store the load data and the displacement data. Considering the risk of network interruption, the latest 100 groups or more of monitoring data can be stored by the data storage unit to support off-network transmission. In addition, in order to avoid packet loss, the wireless gateway can also use forward error correction coding (FEC) to realize transmission data verification to reduce the packet loss rate.

[0070] The wireless communication unit is electrically connected with the data storage unit, and the wireless communication unit is used to send the load data and the displacement data to the wireless gateway. Optionally, the wireless communication unit can be an existing ZigBee communication module, preferably a ZigBee communication module with power consumption less than 1 mW, which can form a Mesh ad hoc network and communicate with the wireless gateway.

[0071] The voltage stabilizing unit is used to convert the voltage output by the electric energy storage unit into a stable voltage, and provide a stable power supply for the load sensor, the distance sensor, the temperature sensor, the data storage unit and the wireless communication unit.

[0072] In some embodiments, each monitoring module can further include a thermoelectric power generation unit. The thermoelectric power generation unit is arranged on the pipe of the pipe system to generate electric energy by utilizing the temperature difference between the pipe surface and the environment. Accordingly, the electric energy storage unit can be charged by the electric energy generated by the thermoelectric power generation unit, so that the battery does not need to be replaced frequently.

[0073] Optionally, the thermoelectric power generation unit can be a thermoelectric power generation unit based on a PN junction thermoelectric material (such as Bi2Te3), which can convert heat energy into electric energy. It should be noted that since the pipe system is usually made of metal, the temperature difference between the pipe surface and the environment is large, even as high as 50℃ or more, so that sufficient electric energy can be generated by utilizing the temperature difference to power the entire monitoring module. Not only is the installation convenient, but the cable laying required for wired power supply is also eliminated, and many maintenance work in the later stage is also eliminated, so that the monitoring module can be installed and used immediately.

[0074] The embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed by the embodiments, since it corresponds to the method disclosed by the embodiments, the description is relatively simple, and the related parts can be referred to the method part.

[0075] The skilled person can further realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized in electronic hardware, computer software or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the components and steps of the examples have been described in the above description in general terms. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0076] The steps of the method or algorithm described in combination with the embodiments disclosed herein can be directly implemented by hardware, a software module executed by a processor, or a combination of the two. The software module can be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0077] It can be understood that the above embodiments only express the preferred embodiments of the present application, which are described more specifically and in detail, but cannot be understood as a limitation to the patent scope of the present application; it should be pointed out that the above technical features can be freely combined without departing from the concept of the present application for those skilled in the art, and several modifications and improvements can be made, which all belong to the protection scope of the present application; therefore, any equivalent transformation and modification made to the patent claim scope of the present application shall belong to the coverage of the patent claim of the present application.

Claims

1. A method for wireless monitoring and digital twin of in-service condition of a pipeline system, characterized in that, The method comprises the following steps: establishing a communication connection with each monitoring module through a wireless communication network; wherein the wireless communication network is composed of multiple wireless gateways, and the monitoring module is arranged on a preset monitoring point of the pipeline system and senses monitoring data of the corresponding monitoring point; spatiotemporal synchronization control of each monitoring module; acquiring sensing data output by each monitoring module after synchronization; real-time structural mechanics simulation of the actual operating state of the pipeline system according to the monitoring data of each monitoring module to realize digital twinning of the actual operating state of the pipeline system; diagnostic processing according to the digital twinning result and output of the diagnostic result.

2. The method of wireless monitoring of in-service conditions of piping systems and digital twinning of claim 1, wherein, The spatiotemporal synchronization control of each monitoring module comprises: broadcasting a time stamp to each wireless gateway; controlling the wireless gateway to send a time correction pulse to the corresponding wireless gateway in a TDMA time slot allocation manner, so that each monitoring module is synchronized.

3. The method of wireless monitoring of in-service conditions of piping systems and digital twinning of claim 1, wherein, In the step of acquiring the sensing data output by each monitoring module after synchronization, it further comprises: constructing a minimum spanning tree topology according to the distribution of each monitoring module, and acquiring the sensing data output by each monitoring module based on the minimum spanning tree topology.

4. The method of wireless monitoring of in-service conditions of piping systems and digital twinning of claim 2, wherein, In the step of acquiring the sensing data output by each monitoring module after synchronization, it further comprises: real-time monitoring of the interference intensity of the default frequency band; judging whether the interference intensity is greater than a preset intensity threshold; when the interference intensity is greater than the preset intensity threshold, controlling the communication frequency band of the wireless communication network to switch to a backup frequency band; wherein the default frequency band includes 2.4 GHz or 5.8 GHz, and the backup frequency band includes 868 MHz or 915 MHz.

5. The method of wireless monitoring of in-service conditions of piping systems and digital twinning according to any one of claims 1 to 4, characterized in that, The monitoring data includes load data, displacement data and temperature data; The real-time structural mechanics simulation of the actual operating state of the pipeline system according to the monitoring data of each monitoring module to realize digital twinning of the actual operating state of the pipeline system comprises: establishing a finite element model based on the finite element method and the pipeline system; mapping all preset monitoring points of the pipeline system to corresponding nodes in the finite element model respectively; inputting the monitoring data of each monitoring module into the finite element model to obtain the actual operating state data of the pipeline system through real-time calculation and analysis; The diagnostic processing according to the digital twinning result comprises: defect identification processing and trend prediction processing of each pipe section according to the actual operating state data.

6. The method of wireless monitoring of in-service conditions of piping systems and digital twinning of claim 5, wherein, The actual operating state data includes displacement change data of each pipe section in the pipeline system, load change data and displacement change data of each rigid support hanger on each pipe section, load change data and spring displacement change data of each spring support hanger on each pipe section, and expansion change data and temperature change data of each guide support hanger on each pipe section; The defect identification processing comprises: According to the actual operation state data, the following processing is performed: when it is judged that the load variation of all the supports and hangers on the pipe section within a first set time is greater than a load instantaneous fluctuation threshold and it is judged that the displacement variation of the pipe section within the first set time is greater than a displacement instantaneous fluctuation threshold, it is determined that the pipe section has transient impact; when it is judged that the load of all the supports and hangers and the displacement of the pipe section within a second set time have both appeared continuous fluctuation, it is determined that the pipe section has steady-state vibration; when it is judged that the load of the spring support and hanger is greater than an overload threshold, it is determined that the spring support and hanger is overloaded; and the expansion and temperature change curve of the guide support and hanger is fitted, the expansion and temperature change curve is compared with a preset expansion amount comparison curve, and it is determined according to the comparison result whether the pipeline has expansion.

7. The method of wireless monitoring of in-service conditions of piping systems and digital twinning of claim 6, wherein, The trend prediction processing includes: According to the actual operation state data, the following processing is performed: fitting the real-time curve of the load and displacement change of each spring support and hanger, obtaining a plurality of real-time curves, comparing each real-time curve with the corresponding theoretical curve, and determining according to the comparison result whether the spring stiffness of each spring support and hanger has a spring stiffness deviation trend; judging whether the settlement amount of the displacement of the pipe section within a third set time is greater than a first settlement threshold and whether the settlement amount of the displacement of the pipe section within a fourth set time is greater than a second settlement threshold, and if any of the judgment results is yes, it is determined that the pipe section has a sinking trend.

8. The method of wireless monitoring of in-service conditions of piping systems and digital twinning of claim 7, wherein, The pipeline system service state wireless monitoring and digital twin method further includes: establishing a three-dimensional model of the pipeline system; highlighting the preset monitoring points in the three-dimensional model that have defects and abnormal trends based on the diagnosis result.

9. A pipeline system service condition wireless monitoring and digital twin system, characterized in that, It includes a monitoring platform, a plurality of wireless gateways and a plurality of monitoring modules; Each monitoring module is arranged on a preset monitoring point of the pipeline system to sense monitoring data of the corresponding monitoring point and send the monitoring data in a wireless communication mode; Each wireless gateway constitutes a wireless communication network, which is in communication connection with each monitoring module and is used for sending the monitoring data sensed by each monitoring module to the monitoring platform; The monitoring platform includes a processor, which realizes the pipeline system service state wireless monitoring and digital twin method according to any one of claims 1 to 8 when executing a computer program.

10. The in-service wireless monitoring and digital twin system of claim 9, wherein, The monitoring module includes a load sensor, a distance measuring sensor, a temperature sensor, an electric energy storage unit, a data storage unit, a wireless communication unit and a voltage stabilizing unit; The load sensor is arranged on the preset monitoring point to sense the load received by the corresponding preset monitoring point and output load data; The distance measuring sensor is arranged on the preset monitoring point to sense the displacement of the corresponding preset monitoring point and output displacement data; The temperature sensor is arranged on the preset monitoring point to sense the temperature of the corresponding preset monitoring point and output temperature data; The electric energy storage unit is used to output a power supply voltage; The data storage unit is electrically connected with the load sensor and the distance sensor, and is configured to store the load data and the displacement data; The wireless communication unit is electrically connected with the data storage unit, and is configured to send the load data and the displacement data to the wireless gateway; The voltage stabilizing unit is electrically connected with the load sensor, the distance sensor, the temperature sensor, the electric energy storage unit, the data storage unit and the wireless communication unit, and is configured to convert the voltage output by the electric energy storage unit into a stable voltage and supply power to each unit.

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